This project analyzes the content categories of Social Buzz, a fictional social media company, to identify the top 5 categories with the largest aggregate popularity using Excel.

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I have recorded a step-by-step video tutorial that demonstrates the entire analysis process.

Audit of their big data practice.

Recommendations for a successful IPO.

Analysis of their content categories to highlight the top 5 categories with the largest aggregate popularity.

Data Understanding: Thoroughly understanding the data model and the business domain.

Data Cleaning: Cleaning the available datasets and designing an ideal dataset for the problem.

Data Modeling: Processing and modelling the data to answer business questions precisely.

Data Analysis: Using analytical techniques to uncover insights and create visualizations to describe these insights.

Visualization: Creating visual representations of the data insights.

Microsoft Excel

From the data, we identified 16 unique categories of posts. The top 5 categories by aggregate popularity are:

Animals: 74,965

Science: 71,168

Healthy Eating: 69,339

Technology: 68,738

Food: 66,676

Animal Content: High engagement with 1,897 reactions.

Seasonal Trends: January is the most common month for posts, aligning with post-holiday activity.

Health Conscious Users: Strong interest in healthy eating content.